try chess use-case only

app.py

@@ -52,24 +52,32 @@ class BasicAgent:
         self.handle_parsing_errors: bool = handle_parsing_errors
         self.max_iterations: int = max_iterations
         self.memory: Optional[ConversationSummaryMemory] = memory
+        self.agent_obj = AgentExecutor(
+            agent=self.agent,
+            tools=self.tools,
+            verbose=self.verbose,
+            handle_parsing_errors=self.handle_parsing_errors,
+            max_iterations=self.max_iterations,
+            memory=self.memory
+        )
 
 
     def is_retriable(self, e: Exception) -> bool:
         # Adjust this check if your error type is different
         return isinstance(e, genai.errors.APIError) and getattr(e, "code", None) in {429, 503}
 
-    def invoke_with_retry(self, agent_obj, question: str, max_retries: int = 5, initial_delay: float = 10.0) -> str:
+    def invoke_with_retry(self,question: str, max_retries: int = 5, initial_delay: float = 10.0) -> str:
         delay = initial_delay
         for attempt in range(max_retries):
             try:
-                result = agent_obj.invoke(
+                result = self.agent_obj.invoke(
                     {"input": question},
                     config={"configurable": {"session_id": "test-session"}},
                 )
                 return result['output']
             except Exception as e:
                 if self.is_retriable(e):
-                    print(f"Quota error (attempt {attempt+1}/{max_retries}), retrying in {delay} seconds...")
+                    print(f"Quota error (attempt {attempt+1}/{max_retries}), retrying in {delay} seconds...",flush=True)
                     time.sleep(delay)
                     delay *= 2  # Exponential backoff
                 else:
@@ -80,22 +88,8 @@ class BasicAgent:
         """
         Allows the instance to be called directly to get an AgentExecutor.
         """
-        agent_obj = self.create_agent_helper()
-        return self.invoke_with_retry(agent_obj, question)
-
-
-    def create_agent_helper(self) -> AgentExecutor:
-        """
-        Creates and returns an AgentExecutor instance.
-        """
-        return AgentExecutor(
-            agent=self.agent,
-            tools=self.tools,
-            verbose=self.verbose,
-            handle_parsing_errors=self.handle_parsing_errors,
-            max_iterations=self.max_iterations,
-            memory=self.memory
-        )
+        #agent_obj = self.create_agent_helper()
+        return self.invoke_with_retry(question)
 
 
 
@@ -177,7 +171,9 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
 
     If you have sufficient information and can provide a CONCISE response, or if no tool is needed, you MUST use this precise format:
-
+    if you can use a LLM to answer the question, think step-by-step and then answer the question.
+    Example: given a chess board image and asked to predict the next best move, if Multi-modal LLM is available, you can use it to answer the question.
+    
     Thought: I have enough information, or no tool is needed.
     Final Answer: [your concise response here]
 
@@ -285,11 +281,11 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             full_question_for_agent += f"\n\nAttachment '{file_name}' available at EXACT URL: {attachment_url}"
             #print(f"Running agent on task {task_id}: {full_question_for_agent}",flush=True)
         
-        '''
-        if task_id != "1f975693-876d-457b-a649-393859e79bf3":
+        
+        if task_id != "cca530fc-4052-43b2-b130-b30968d8aa44":
             print("NFLUSH Skip tasks that are not the specific one we want to run", flush=True)
             continue  # Skip tasks that are not the specific one we want to run
-        '''
+        
         try:
             time.sleep(5)  # Add a 5 sec delay before running the agent
             submitted_answer = agent(full_question_for_agent)